A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.;Front Cover -- Dedication -- Preface to Second Edition -- Preface to First Edition -- List of Figures -- List of Tables -- Contents -- Chapter 1: An Introduction to R -- Chapter 2: Data Analysis Using Graphical Displays: Malignant Melanoma in the USA and Chinese Health and Family Life -- Chapter 3: Simple Inference: Guessing Lengths, Wave Energy, Water Hardness, Piston Rings, and Rearrests of Juveniles -- Chapter 4: Conditional Inference: Guessing Lengths, Suicides, Gastrointestinal Damage, and Newborn Infants -- Chapter 5: Analysis of Variance: Weight Gain, Foster Feeding in Rats, Water Hardness and Male Egyptian Skulls -- Chapter 6: Simple and Multiple Linear Regression: How Old is the Universe and Cloud Seeding -- Chapter 7: Logistic Regression and Generalised Linear Models: Blood Screening, Women's Role in Society, Colonic Polyps, and Driving and Back Pain -- Chapter 8: Density Estimation: Erupting Geysers and Star Clusters -- Chapter 9: Recursive Partitioning: Predicting Body Fat and Glaucoma Diagnosis -- Chapter 10: Scatterplot Smoothers and Generalised Additive Models: The Men's Olympic 1500m, Air Pollution in the USA, and Risk Factors for Kyphosis -- Chapter 11: Survival Analysis:Glioma Treatment and Breast Cancer Survival -- Chapter 12: Analysing Longitudinal Data I:Computerised Delivery of Cognitive Behavioural Therapy -- Beat the Blues -- Chapter 13: Analysing Longitudinal Data II -Generalised Estimation Equations and Linear Mixed Effect Models: Treating Respiratory Illness and Epileptic Seizures -- Chapter 14: Simultaneous Inference and Multiple Comparisons: Genetic Components of Alcoholism, Deer Browsing Intensities, and Cloud Seeding -- Chapter 15: Meta-Analysis: Nicotine Gum and Smoking Cessation and the Efficacy of BCG Vaccine in the Treatment of Tuberculosis -- Chapter 16: Principal Component Analysis: The Olympic Heptathlon.